Improved ABC Algorithm Optimizing the Bridge Sensor Placement
AbstractInspired by sensor coverage density and matching & preserving strategy, this paper proposes an Improved Artificial Bee Colony (IABC) algorithm which is designed to optimize bridge sensor placement. We use dynamic random coverage coding method to initialize colony to ensure the diversity and effectiveness. In addition, we randomly select the factors with lower trust value to search and evolve after food source being matched in order that the relatively high trust point factor is retained in the exploitation of food sources, which reduces the blindness of searching and improves the efficiency of convergence and the accuracy of the algorithm. According to the analysis of the modal data of the Ha-Qi long span railway bridge, the results show that IABC algorithm has faster convergence rate and better global search ability when solving the optimal placement problem of bridge sensor. The final analysis results also indicate that the IABC’s solution accuracy is 76.45% higher than that of the ABC algorithm, and the solution stability is improved by 86.23%. The final sensor placement mostly covers the sensitive monitoring points of the bridge structure and, in this way, the IABC algorithm is suitable for solving the optimal placement problem of large bridge and other structures. View Full-Text
Share & Cite This Article
Yang, J.; Peng, Z. Improved ABC Algorithm Optimizing the Bridge Sensor Placement. Sensors 2018, 18, 2240.
Yang J, Peng Z. Improved ABC Algorithm Optimizing the Bridge Sensor Placement. Sensors. 2018; 18(7):2240.Chicago/Turabian Style
Yang, Jianhui; Peng, Zhenrui. 2018. "Improved ABC Algorithm Optimizing the Bridge Sensor Placement." Sensors 18, no. 7: 2240.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.